Hvac performance monitoring system

ABSTRACT

The present invention relates to environmental control systems. More particularly, the present invention relates to methods and apparatus for monitoring the performance of environmental control systems arranged to control at least one environmental characteristic in an environment. The method comprises: identifying an activation period during which the environmental control system is expected to be activated to control an environmental characteristic; recording a data set of sensor data measured during the activation period relating to the environmental characteristic; receiving control data indicating a target value configured at the environmental control system for the environmental characteristic; analysing the sensor data set in dependence on the target value to determine whether the sensor data is consistent with an expected response of the environmental characteristic during the activation period; and detecting an underperformance condition in response to determining that the sensor data is not consistent with the expected response.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a national phase application of InternationalApplication No PCT/GB2017/053156, filed Oct. 18, 2017, which claimspriority to Great Britain Patent Application Serial No. 1617877.4, filedOct. 21, 2016, all of which are incorporated herein by reference.

BACKGROUND

The present invention relates, but is not limited, to systems andmethods for monitoring environmental control systems. More particularly,the present invention relates to determining faults in heating,ventilation and air conditioning (HVAC) systems.

HVAC systems can fail catastrophically, for example if the boiler breakswhile the house is unoccupied during the day. A user may only realisethat this has happened when they return home to a cold house. It willlikely be the following day before an engineer can be requested.

Alternatively HVAC systems can degrade over time, leading tounderperformance of the HVAC system. Components can fail lesscatastrophically, for example leading to leakage between heating systemscircuits. Other systems might be incorrectly installed, but the user maynot be aware of this.

One example of an underperformance is when a central heating systemappears to function normally but is unable to achieve or maintain adesired target temperature.

One approach to monitoring a central heating boiler involves obtaininginternal diagnostic information from the boiler in order to predict whenthe boiler has failed. However, this requires a suitably equipped boilerwith inbuilt diagnostics and communications functionality.

SUMMARY

Embodiments of the invention seek to address some of the deficiencies ofknown approaches to monitoring HVAC performance.

Aspects of the invention are set out in the independent claims andpreferred features are set out in the dependent claims.

There is described herein a method of monitoring the performance of anenvironmental control system arranged to control at least oneenvironmental characteristic in an environment, the method comprising:identifying an activation period during which the environmental controlsystem is expected to be activated to control an environmentalcharacteristic; recording a data set of sensor data measured during theactivation period relating to the environmental characteristic;receiving control data indicating a target value configured at theenvironmental control system for the environmental characteristic;analysing the sensor data set in dependence on the target value todetermine whether the sensor data is consistent with an expectedresponse of the environmental characteristic during the activationperiod; and detecting an underperformance condition in response todetermining that the sensor data is not consistent with the expectedresponse.

An activation period preferably refers to the time for which theenvironmental control system, or a component thereof, is in operation toalter or maintain the environmental characteristic, or during which thesystem or component should ordinarily be in operation (e.g. as indicatedby a control signal or schedule), even if it is not actually active(e.g. due to a fault). An activation period may also be referred to asan “operational period”.

Preferably identifying the activation period comprises detecting thestart and/or end of the activation period.

Preferably one or both of the start and end of the activation period aredetected in dependence on a control signal used to control theenvironmental control system.

Preferably the control signal is a control signal for controlling acomponent of the environmental control system adapted to influence theenvironmental characteristic. Preferably the component is a heating orcooling device. The component may be one of: a boiler; an airconditioning unit; a furnace; a heat pump; a fan; and a dehumidifier.For example, where the environmental control system is configured toregulate room temperature, the control signal may be a “call for heat”signal. The call for heat signal may be directed to a boiler. The sensordata may be, for example, one of: temperature; water temperature;pressure; and humidity. Where the sensor data is temperature data, itmay refer to: water temperature, or room or other ambient temperature;e.g. if a boiler heats domestic hot water, the water temperature in orexiting a hot water tank may be suitable and if a boiler heats aswimming pool, the pool water temperature may be measured.

The control signal may be received from a control component of theenvironmental control system, preferably from a thermostat.

Preferably one or both of the start and end of the activation period aredetected in dependence on a change in the target value specified in thecontrol data and/or a difference between the target value and a currentvalue of the environmental characteristic. In other words, it may beinferred that the system or component should be active instead of or inaddition to relying on a specific activation signal.

Preferably the method comprises one or both of: inferring the start ofthe activation period in response to detecting a current measured valueof the environmental control characteristic not meeting the targetvalue; and/or inferring the end of the activation period in response todetecting a current measured value of the environmental controlcharacteristic meeting the target value. For example, for a heatingsystem, meeting the target value may mean that a measured temperature isequal to or exceeds the target value. Whereas for a cooling or airconditioning system, meeting the target value may be when thetemperature is equal to or falls below the target.

For example, the method comprises detecting the start of the activationperiod, for a heating system, in response to identifying an increase ina target temperature above a currently measured temperature or, for acooling system, in response to identifying a decrease in targettemperature below a currently measured temperature.

In some embodiments, receiving control data comprises accessing acontrol schedule configured at the environmental control system, thecontrol schedule specifying one or more control set points, each controlset point specifying a target value for the environmental characteristicapplicable at a respective time. The respective time may be point intime or it may be a time period.

Preferably detecting the start and/or end of the activation is periodbased on the control schedule.

Preferably the environmental characteristic is a temperature of theenvironment. A control set point or target value may specify a targettemperature for the environment.

Preferably the analysed data set additionally includes one or both of:sensor data for a period preceding (preferably immediately preceding)the start of the activation period; sensor data for a period following(preferably immediately following) the end of the activation period. Inthis case the analysis to determine expected behaviour may be extendedto consider the whole measurement period (i.e. including the activationperiod and the preceding and/or following periods), e.g. to determinewhether the sensor data is consistent with the expected response overall or part of the measurement period including the activation periodand the preceding and/or following periods.

Preferably the method includes periodically recording sensor datarelating to the environmental characteristic from at least oneenvironmental sensor in a sensor log; and, in response to identifyingthe activation period, generating the data set for analysis based on thesensor log.

Preferably the method further comprises, in response to identifying thestart of the activation period: adding previously recorded sensor datafor a predetermined duration prior to the start of the activation periodfrom the log to the data set for analysis; adding further sensor datareceived during the activation period to the data set; after detectionof the end of the activation period, continuing to store sensor datareceived from the environmental sensor to the data set; and terminatingrecording of sensor data to the data set a predetermined duration afterthe end of the activation period.

The predetermined durations or time periods before and/or after theactivation period may be equal or they may be different. Thepredetermined durations may be around 5 minutes, 10 minutes, 20 minutes,40 minutes or one hour. Preferably the predetermined durations arebetween 20 and 40 minutes. More preferably the predetermined durationsare around 30 minutes.

After terminating recording of sensor data, the method may furthercomprise continuing to record environmental sensor in the sensor log.

Preferably the analysing step comprises determining whether the sensordata indicates that the target value is substantially attained and/ormaintained during the activation period.

Preferably the detecting step comprises detecting an underperformancecondition in response to the target value not being substantiallyattained and/or maintained during the activation period.

Preferably the analysis of the sensor data determines underperformanceconditions based on one or more of: a duration of the activation period;a change of the environmental characteristic over the course of theactivation period; a rate of change of the environmental characteristicduring the activation period, preferably determined at or near thebeginning of the period and/or at or near the end of the period; adifference between one or more measured values of the environmentalcharacteristic during the activation period and the target value, and/oran average or integral of said difference over the activation period. Insome embodiments the determination of underperformance conditions mayalternatively or additionally be based on sensor measurements (e.g.temperature) over the activation period, such as the time to the minimumand maximum temperature. For example, if the minimum temperature isreached late in the heating period this can suggest that there is aproblem.

The determination of underperformance conditions may also oralternatively be based on the average rate of change of theenvironmental characteristic over the activation period.

Preferably analysing the sensor data to determine whether the sensordata is consistent with an expected response of the environmentalcharacteristic during the period comprises determining whether thesensor data meets at least one of a set of one or more predeterminedfault conditions.

Preferably the environmental characteristic is temperature, thepredetermined fault conditions comprising one or more of: detecting alack of increase in temperature or a reduction in temperature during theactivation period, the activation period intended to increase thetemperature; detecting a lack of reduction in temperature or an increasein temperature during the activation period, the activation periodintended to reduce the temperature; detecting a steady state temperatureachieved or maintained during the activation period which differs from atarget value specified in a control schedule, preferably by more than athreshold amount; detecting a temperature change indicative ofactivation of the environmental control system in a period immediatelypreceding or following the activation period; detecting an irregularpattern of temperature variation during the activation period; detectinga correlation between environmental temperature variations during theactivation period and the operation of, or a control signal intended forthe operation of, a system other than an environmental temperaturecontrol component intended to regulate the environmental temperature,preferably wherein the other system is for heating of water in a hotwater supply system for supplying heated water to water outlets.

Preferably the method further comprises alerting a user associated withthe environmental control system in response to detecting theunderperformance condition, the alerting preferably comprising one ormore of: displaying an alert on a display associated with theenvironmental control system; and transmitting an alert message to auser device associated with the user, preferably a personal or mobilecomputing or communications device. The message may indicate what sortof repair or maintenance is required, and may provide a user or engineerwith information relating to the underperformance condition which helpsto diagnose a fault. The message may also give the user the option ofautomatically requesting an engineer or repair service.

Preferably the method further comprises classifying an underperformancecondition of the environmental control system based on one or more of: aseverity of the condition, and a type of the condition; and alerting auser and/or a service/support operator in dependence on theclassification.

Preferably the method comprises, in response to detecting theunderperformance condition, initiating a test procedure for testing theenvironmental control system.

Preferably the test procedure comprises: activating the environmentalcontrol system, the activating optionally overriding a control scheduleactive for the environmental control system, measuring changes in theenvironmental characteristic in response to activation of theenvironmental control system; and performing further analysis ofmeasured sensor data relating to the environmental characteristic toidentify, quantify and/or classify the underperformance condition.

Preferably the method is performed at a data analysis system andcomprises the steps of: receiving from the environmental control systemover a computer network, e.g. a Wide Area Network (WAN) such as theInternet, one or more of: sensor data relating to the environmentalcharacteristic, environmental control system control signals, andcontrol schedule data; and performing the analysis based on the receiveddata.

Preferably the method further comprises performing the analysis by ananalysis module asynchronously with the data collection.

Preferably the method comprises at a data collection module: detectingthe activation period and storing the sensor data set relating to theactivation period in a data object; and at an analysis module: receivingthe data object and performing the analysis of the sensor data;preferably wherein the data analysis transmits the data object or areference thereto to the analysis module via a message queue.

Preferably the data collection module comprises a plurality of datacollection processes or threads operating in parallel, the methodcomprising receiving data from each of a plurality of environmentalcontrol systems at a respective data collection process or thread.

Preferably detecting correct operation of the environmental controlsystem in response to determining that the sensor data is consistentwith the expected response, preferably if the environmentalcharacteristic changes responsive to activation at a rate correspondingto a predetermined expected rate and/or if the environmentalcharacteristic reaches a steady state value during the activation periodconsistent with the target value.

Preferably the method comprises creating a model of expected behaviourbased on activation periods identified following analysis asrepresenting correct operation of the environmental control system, andusing the model to determine underperformance in later activationperiods.

In preferred embodiments, analysing the sensor data set in dependence onthe target value to determine whether the sensor data is consistent withan expected response of the environmental characteristic during theactivation period, comprises determining a plurality of parameters basedon the sensor data set, the parameters preferably relating to operationand/or performance of the environmental control system and/or thecontrolled environment, and applying a classification model to theparameters, the classification model arranged to classify the activationperiod based on the parameters (e.g. as exhibiting expected or abnormalbehaviour). The classification model is preferably generated (e.g. usinga machine learning/regression technique) based on a set of trainingsamples (which may relate to the environmental control system and/or toone or more other environmental control systems installed at otherlocations).

Preferably the method comprises, in response to determining that thedata set is consistent with the expected response, analysing the dataset to determine one or more thermal parameters of the environmentalcontrol system and/or the associated environment, and using the one ormore thermal parameters in the analysing step for a subsequentactivation period, the one or more thermal parameters optionallyincluding an expected rate of change of the environmental characteristicresponsive to activation of the environmental control system. In someembodiments data quality is also monitored. If the monitoring system isproviding data of too low a quality (e.g. missing data points etc.),then the user can be alerted that the monitoring system might not beadequately installed.

There is also described herein a monitoring system having means (e.g. inthe form of a processor with associated memory) for performing a methodas set out above.

According to another aspect, there is described an environmental controlsystem arranged to control at least one environmental characteristic inan environment, the device comprising: means for identifying anactivation period during which the environmental control system isexpected to be activated to control an environmental characteristic;means for recording a data set of sensor data measured during theactivation period relating to the environmental characteristic; andmeans for transmitting the data set to an analysis server for analysis.

There is also described an analysis server for monitoring theperformance of an environmental control system arranged to control atleast one environmental characteristic in an environment, the servercomprising: means for receiving from a monitoring device associated withthe environmental control system a data set of sensor data relating tothe environmental characteristic measured during an activation period ofthe environmental control system; means for receiving control dataindicating a target value configured at the environmental control systemfor the environmental characteristic; means for analysing the sensordata set in dependence on the target value to determine whether thesensor data is consistent with an expected response of the environmentalcharacteristic during the activation period; and means for detecting anunderperformance condition in response to determining that the sensordata is not consistent with the expected response.

Preferably the device or server may be arranged to perform orparticipate in a method as set out above.

There is also described a tangible, non-transitory computer-readablemedium comprising software code adapted, when executed on a dataprocessing apparatus, to perform a method as set out above.

Where reference is made above to means for performing a given processingstep, such means may be provided in the form of a processor withassociated memory (e.g. storing software code for execution by theprocessor).

Any feature in one aspect of the invention may be applied to otheraspects of the invention, in any appropriate combination. In particular,method features may be applied to system aspects, and vice versa.Furthermore, any, some and/or all features in one aspect can be appliedto any, some and/or all features in any other aspect, in any appropriatecombination.

It should also be appreciated that particular combinations of thevarious features described and defined in any aspects of the inventioncan be implemented and/or supplied and/or used independently.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments will now be described, by way of example only and withreference to the accompanying drawings, in which:

FIG. 1 illustrates a system diagram of an exemplary environmentalcontrol and monitoring system;

FIG. 2 is a flow diagram of an exemplary process for monitoring anenvironmental control system;

FIG. 3 is a flow diagram of an exemplary process for collecting data inan environmental control monitoring system;

FIG. 4 is a timing chart showing an exemplary data collection processfor the creation of a record relating to an operational period of anHVAC component;

FIG. 5 is a flow diagram of an exemplary process for identifying“normal” system behaviour in an HVAC or environmental control monitoringsystem;

FIG. 6 is a flow diagram of an exemplary process for identifying faultsin an HVAC monitoring system;

FIG. 7 is a diagram showing an exemplary classification of differentfault types in an HVAC or environmental control system;

FIG. 8 is a plot showing an exemplary temperature data set indicative ofa complete boiler failure;

FIG. 9 is a plot showing an exemplary temperature data set indicative ofinverted wiring;

FIG. 10 is a plot showing an exemplary temperature data set for anunderpowered or incorrectly balanced environmental control system;

FIG. 11 is a plot showing an exemplary temperature data set for anenvironmental control system in which the room temperature is affectedby calls for Domestic Hot Water;

FIG. 11B is a plot showing an exemplary temperature data set for aheating system that is operating normally;

FIG. 12 is a flow diagram showing an exemplary process for informing theuser of a fault that has been identified in an environmental controlsystem;

FIG. 13 is a flow diagram showing an exemplary test procedure foranalysing faults in an environmental control system;

FIG. 14 illustrates the hardware architecture of an exemplary device formonitoring an HVAC or environmental control system;

FIG. 15A illustrates the hardware architecture of an exemplarydatacentre for monitoring HVAC or environmental control systems; and

FIG. 15B illustrates the software architecture of an exemplarydatacentre for monitoring HVAC or environmental control systems.

DETAILED DESCRIPTION

Particular embodiments provide a method and/or device which monitors theenvironment of a house or other building in order to determine an HVACsystem failure. By automatically detecting faults, the mean time torepair the system can be reduced. Using this device and/or method it ispossible to identify different types of system failure by analysing howone or more characteristics of the house or building environment behave.For example, by monitoring the performance of the thermal environment(i.e. the temperature over time) it is possible to determine faults in aboiler.

It has been unexpectedly found that failures in boilers, heating and airconditioning units can be identified from room temperature measurementsmade by a single temperature sensor. Since only a single temperaturemonitor/sensor is required, the monitoring device can be installed verysimply, for example the monitoring device can be self-installed by theuser as a retrofit.

The method and/or device can monitor all aspects of the HVAC system andthe thermal performance of the house. The monitoring method and/ordevice can provide the ability to monitor how the environment respondsto the activity of the HVAC device (e.g. a boiler), rather thanmeasuring the operation of the HVAC device directly.

The monitoring method and device may be able to identify subtle modes offailure which might not be obvious to an occupant.

The present invention can be provided in an HVAC monitoring device whichmonitors the internal room temperature and knows the scheduled targettemperature (i.e. the temperature selected by the user). By monitoringthis data it may be possible to reveal a number of failure modes, someof which are described below.

In a further aspect, on detection of a failure the monitoring device mayalert the user with relevant information and might propose a testprocedure relevant to the issue detected. The user can then choose torun the test. In one embodiment, functionality is provided forperforming a heating test cycle to confirm whether or not a failure hasactually occurred. In order to run such a test, the HVAC monitoringdevice may be able to activate the HVAC unit either directly (via apower control signal to a relay switch) or via manipulation of thetarget temperature.

Following the positive outcome of the test an engineer can be requestedand given prior knowledge of the system's determined mode of failure.

While parts of the following description relate to a heating system anda boiler in particular, use of the described techniques in other typesof environmental control systems such as a cooling, a humiditycontrolled ventilation system and an air conditioning system, forexample, is also contemplated.

FIG. 1 illustrates a system diagram of an exemplary environmentalcontrol and monitoring system 100. The HVAC control and monitoringsystem 100 includes an HVAC monitoring device 110 installed in a user'spremises. The HVAC monitoring device 110 is wirelessly connected to atemperature sensor 112 and a humidity sensor 114 installed within theuser's premises. However the sensors 112, 114 may be combined in theHVAC monitoring device 110. Alternatively the sensors 112,114 maycommunicate with the HVAC monitoring device 110 via wired connections.

The HVAC monitoring device 110 is in wireless communication with an HVACcontroller 120. The HVAC controller 120 may be, for example, a smartthermostat into which a user can program a heating, hot water or otherenvironmental control schedule. Of course, the HVAC monitoring device110 itself (optionally, along with the temperature sensor 112 andhumidity sensor 114) could be incorporated into the HVAC controller 120,and/or may make use of one or more sensors (e.g. temperature and/orhumidity) already provided in the thermostat.

The HVAC monitoring device 110 and HVAC controller 120 are connectedwirelessly to the user's local network/internet access infrastructure,for example, to a wireless or wired home router/access point 150, whichin turn provides access to the Internet 170 through a modem 160, such asan ADSL or fibre modem. Depending on access technology, router 150 andmodem 160 may be combined in a single device or replaced with otheraccess devices appropriate to the access technology. Some embodimentsmay provide an additional hub device (not shown), e.g. connected to theboiler (incorporating wireless receiver 130), to manage the HVAC systemand coordinate between the components, store control/configuration data(e.g. heating schedules), and the like (such functionality mayalternatively be implemented in the HVAC controller 120).

The HVAC controller 120 is wirelessly connected to three wirelessreceivers 130, 132, 134. One wireless receiver 130 is connected by awired connection to a central heating/hot water boiler 140, anotherwireless receiver 132 is connected by a wired connection to aventilation system 142 and the third wireless receiver 134 is connectedby a wired connection to an air conditioning system 144. The boiler 140may, for example, be a conventional gas boiler arranged to provide asupply of heated water to a series of radiators in the user's premisesand to a hot water tank for onward supply to hot water taps. Theventilation system 142 may be, for example, a humidity controlledventilation system.

Although three HVAC components 140, 142, 144 (and therefore threewireless receivers 130, 132, 134) are shown, in some embodiments onlyone or two HVAC components may be provided, whilst in other embodimentsthere may be more and/or different HVAC components with wirelessreceivers which can communicate wirelessly with the HVAC controller 120.In some embodiments the wireless receivers can be included in the HVACcomponents, such as the boiler or air conditioning system, rather thanbeing provided as separate devices.

The HVAC controller 120 can store schedule and other informationrelevant to the control information of the HVAC components. The HVACcontroller 120 can then send control and/or schedule information to thewireless receivers 130, 132, 134. For example the user can program aschedule for hot water at the HVAC controller 120, and the HVACcontroller 120 can then send the hot water schedule to the wirelessreceiver 130. The wireless receiver 130 can then use the schedule andtemperature information received from the HVAC controller 120 to turnthe boiler 140 on or off as needed. Alternatively, the HVAC controller120 may send a control signal to the wireless receiver 130 to instructthe boiler 140 to start or stop producing hot water each time hot wateris required according to the schedule.

The user can also program space heating or other environmental controlrequirements into the HVAC controller 120. Typically, this involvesprogramming a heating schedule specifying a set of heating set pointsapplicable during respective time periods, each set point defining atarget temperature value to be achieved and maintained during theperiod. For example, the user may request a room temperature of 20° C.between 7 am and 9 am. Other periods in the schedule may be designatedas “off” periods where no heating is required (though the system maynevertheless apply some minimum target e.g. 5° C. during such periods toprotect against frost damage). The HVAC controller 120 receives a roomtemperature reading (either from its own internal temperature sensor, orfrom temperature sensor 112) and can provide control signals to theboiler 140 (via wireless receiver 130) or to the air conditioning system144 (via wireless receiver 134), as appropriate (e.g. to increase ordecrease the temperature back to the scheduled target value).

The user may also interact with the HVAC system from a user device 190located outside the user's premises on an external network and connectedto the Internet 170. In some embodiments a user device 192 is located atthe user premises and can be connected wirelessly (or by wiredconnections) to the user's local network, e.g. as shown the user device192 can be in wireless communication with the HVAC controller 120. Userdevices 190, 192 may take the form of smartphones, tablet computers,personal computers, and the like. User devices may include anapplication for controlling the heating system, for example to create oredit a heating/hot water schedule, switch between manual/scheduledoperation, adjust temperature, activate boost mode, etc. The applicationmay then send information to the HVAC controller 120 as required (e.g.to update a schedule).

The HVAC controller 120 sends to the HVAC monitoring device 110 thecontrol schedule and/or any control commands sent to the HVACcomponents. The temperature sensor 112 and the humidity sensor 114 takereadings frequently, e.g. every 2 minutes, and send the readings to theHVAC monitoring device 110. The HVAC monitoring device 110 can log thereceived schedule, control commands and readings.

The HVAC monitoring device 110 can also alternatively send the controlinformation and sensed information to a remote datacentre such asanalysis server 180 on an external network, e.g. via its connection tothe Internet 170. The remote datacentre 180 can log this information andstore for analysis information ascribed to periods during which HVACcomponents are operating (as described in more detail below).Alternatively, the logging, storage and analysis process can beperformed at the HVAC monitoring device 110, without the need for aremote datacentre 180.

While this description has focused on the home environment, theinvention can also be used in offices or other premises in whichenvironmental conditions such as room temperature and humidity arecontrolled.

Although only a single temperature sensor and a single humidity sensorinstalled in at least one room in the user's premises are describedabove, in some embodiments multiple sensors may be provided at differentlocations within the premises so that more information about theperformance of the HVAC system can be collected. In some cases multiplesensors can improve the accuracy of the monitoring.

It is also possible to position sensors outside the environmentcontrolled by the HVAC system (e.g. air temperature and humidity sensorlocated outside a house). By measuring outside characteristics, it maybe possible to get further insights into the performance of the system(e.g. more heat may be required to maintain a target room temperature ifit is colder outside).

FIG. 2 shows an exemplary method 200 for monitoring anHVAC/environmental control system 100 as described above and shown inFIG. 1. At step 202 the HVAC component is monitored by collecting datarelevant to a series of periods of operation of the HVAC component, forexample the data may be room temperature values and the HVAC componentmay be a boiler 140. The temperature values may be values recordedduring times when the boiler 140 is turned on. They may also includevalues recorded before the boiler 140 has been turned on and after theboiler has been turned off.

At step 204 the data collected in step 202 is analysed to identifypatterns indicative of normal operation of the HVAC component, forexample over a series of heating periods it may be possible to modelnormal operation of the house, such as a pattern showing how long ittakes to increase the room temperature by a certain amount.

At step 206 the HVAC component is monitored by collecting data relevantto a first period of operation (or an activation period) of the HVACcomponent.

At step 208 the collected data is analysed. If the collected datadiverges from a pattern indicative of normal operation by more than acertain amount an underperformance condition such as a suspected faultor failure of the HVAC component may be identified. For example, acontrol signal may have been sent to a boiler to instruct it to switchon to increase the room temperature, however the room temperature maynot increase as per the usual pattern indicative of normal operation. Insome embodiments, this analysis can be performed continuously as newdata arrives, i.e. before the end of an activation period and before thecomplete set of data relevant to the activation period is complete. Thismeans that a failure can be detected before the end of an activationperiod.

At step 210 the user is alerted of the suspected failure of the HVACcomponent. For example, this may be via a notification on a smartphone.

At step 212 a suggestion is given to the user that an appropriate testprocedure of the HVAC component is initiated. The suggested testprocedure may be appropriate to the suspected fault. This may again bevia a notification on a user's smartphone.

If the user accepts or gives permission for the test procedure to goahead, at step 214 a test procedure is initiated. For example, the testprocedure may override the user's heating schedule temporarily and theresulting room temperature may be recorded.

At step 216 the results of the test procedure are collected andanalysed. If the test results confirm that the HVAC component hasfailed, at step 218 a message is sent to the user requesting permissionto call out an engineer. Alternatively, if the test results show that afailure has not occurred, a message will be sent to the user informingthem of this outcome.

In some cases the data collected at step 206 may be sufficient todetermine, at step 208, the specific failure of the HVAC component, suchthat no testing is required. In such a case, the method 200 may proceedfrom step 210 straight to step 218.

In other cases, steps 202 and 204 may be omitted as it may be possibleto identify a suspected fault from a single period of operation, withoutrequiring knowledge of previous operational periods, e.g. by identifyinginherent inconsistencies in the data (such as temperature decreasingdespite heating being on).

The process 300 of collecting data relevant to a period of operation ofan HVAC component will now be described in relation to FIG. 3. Theprocess 300 may be performed at step 206 of FIG. 2.

At step 302 the value of an environmental characteristic is measured atregular time intervals. These time intervals may be predetermined andfixed, or may be configurable. For example, temperature sensor 112 andhumidity sensor 114 may be arranged to record thermal and humidity dataat 2 minute intervals.

At step 304 a log of the values of the environmental characteristic ismaintained. The log may consist of values relating to only a recent timeperiod, for example data collected in the preceding 30 minutes. However,30 minutes is only an example, and the time period of data held in thelog may be adapted, for example 20 minutes' or 40 minutes' worth of datamay be used. As new values are measured, the oldest values will bedeleted and overwritten. The time at which each value is measured willalso be recorded.

At step 306 an indication that an HVAC component has or should have beenactivated (e.g. that the component is, or at least should be, inoperation) is received. For example this could be a signal from the HVACcontroller 120 indicating that it has just instructed the airconditioning system 144 to switch on. In one approach a copy of the“call for heat” control signals sent from the HVAC controller 120 to theboiler 140 (or of an equivalent control signal sent to another HVACcomponent) may be received and that control signal used to identify thestart of an activation period. Alternatively the start of the activationperiod may be inferred from a change in target value (set point)configured in the control schedule and/or the fact that the measuredenvironmental characteristic diverges from the target value by more thana certain amount. For example it may be that the recorded temperature ishigher than the target temperature in the control schedule, so the airconditioning system should be activated. In some embodiments the targettemperature is determined by locating the temperature at which thesystem starts to oscillate.

The indication that an HVAC component is (or should be) in operationtriggers the creation of a record relating to an activation period ofthe HVAC component (step 308). The environmental characteristic valuesheld in the log when the indication of activation is received areincluded in the record. The period of time for which the HVAC device is,or should be, switched on and operational is referred to herein as the“activation period” or “operational period” interchangeably.

In step 310 data indicative of the values of an environmentalcharacteristic at predetermined time intervals continues to be recordedand this data is added to the record relating to the operational periodof the HVAC component.

At step 312 an indication that an HVAC component has been deactivated(i.e. that the component has been, or at least should have been,switched off) is received. For example this could be a signal from theHVAC controller 120 indicating that it has just instructed the airconditioning system 134 to switch off (e.g. based on the “call for heat”or similar control signal as discussed above). Alternatively the end ofthe activation period may be inferred from a change in the controlschedule set point and/or the fact that the recorded environmentalcharacteristic (e.g. temperature) is within the acceptable range in thecontrol schedule.

Following the end of activation of the HVAC component the sensor datacorresponding to the environmental characteristic for a predeterminedperiod continues to be added to the record relating to the activationperiod of the HVAC component (step 314). This subsequent time period maybe equal in length to that of the values stored before the HVACcomponent was operational/activated, e.g. for a 30 minute time periodfollowing the de-activation of the component. However, the subsequenttime period may be adapted. For example it may be at least 5 minutes ornot more than an hour. Other suitable time periods would be around 20minutes or around 40 minutes.

The resultant record of environmental characteristic values obtainedfrom the sensors can be analysed to identify patterns and trends. Thiscan be helpful in identifying “normal” behaviour and also in identifyinga fault or error in the operation of an HVAC device or component, asdescribed in more detail below.

Optionally, steps 302, 304 and/or 314 above may be omitted. Thus, in oneexample, environmental sensor data may be recorded only for the timeperiod during which the HVAC component was actually intended to be inoperation.

In a preferred embodiment the methods 200 and 300 described in relationto FIGS. 2 and 3 are performed at the remote analysis server 180. Forexample in step 302 the environmental characteristic data can bemeasured by a sensor, sent to the HVAC monitoring device 110 as readingsare generated, and then sent to the analysis server 180 (via accesspoint 150 and the Internet 170). When the control and thermal data isreceived by the remote datacentre 180 it is placed on a message queue,and subsequently passed to an analysis module within the remotedatacentre 180 for analysis.

The log can then be maintained at the remote datacentre 180 (step 304),which can construct and store the record (steps 308, 310 & 314) andperform the subsequent analysis. Indications of the activation anddeactivation of the HVAC component (steps 306 & 312) may be sent fromthe HVAC controller 120 directly to the remote analysis server 180 viathe Internet 170, or may be sent to the remote analysis server 180 fromthe HVAC monitoring device 110. Alternatively, the indication of(de-)activation may be inferred at the remote datacentre 180 based onknowledge of the pre-set environmental control schedule and the measuredenvironmental characteristic data.

However, in alternative embodiments some or all of the steps of themethods 200 and 300 may be performed at the HVAC monitoring device 110within the user's premises. In such a case the HVAC monitoring device110 can have sufficient memory and processing power to perform the datacollection and analysis itself, so that it is performed in the user'spremises, which can be helpful if security or lack of communications(e.g. WAN) is a an issue. For example, at step 302 the temperature andhumidity data can be sent to the HVAC monitoring device 110 fortemporary storage. The log mentioned at step 304 may be stored at theHVAC monitoring device 110. Copies of the control signals described instep 306 may be sent from the HVAC controller 120 to the HVAC monitoringdevice 110 (steps 306 & 312). Alternatively, the indication of (de-)activation may be inferred at the HVAC monitoring device 110 based onknowledge of the pre-set environmental control schedule and the measuredenvironmental characteristic data.

The HVAC monitoring device 110 may then create and store (step 308) therecord of environmental characteristic data relating to the operationalperiod. Alternatively, (where only some steps of the method 300 areperformed at the HVAC monitoring device 110) upon receiving anindication of the activation of the HVAC component (step 306), the HVACmonitoring device 110 may send the data values stored in the log to theremote analysis module 180 so that the analysis module 180 can createand store the record relating to the operational period of the HVACdevice (steps 308, 310 & 314).

The rolling log of values of the environmental characteristic may bestored at the remote datacentre 180 only or at both the remotedatacentre 180 and at the HVAC monitoring device 110. In someembodiments the HVAC monitoring device 110 may pass the log onto theremote datacentre 180 as the data is measured and received (e.g. at1-minute intervals), less frequently (every 30 minutes or so), only oncethe indication that an HVAC component has been activated is received atstep 306, or only after detection of both the start and end of anactivation period (step 312).

Similarly, the record relating to the activation period may be recordedonly at the remote datacentre 180, at both the remote datacentre 180 andthe HVAC monitoring device 110 simultaneously, or stored at the HVACmonitoring device as the record is being created and only sent to theremote datacentre 180 once the record is complete.

An activation period of an HVAC component can be detected from a binarymessage stream of control data, e.g. in the case of a boiler, a “boileron” command followed by a consecutive “boiler off” command. Thisdetection (performed at steps 306 and 312 above) may be performed at theremote datacentre 180 or at the HVAC monitoring device 110. If thecontrol signal command is not available, the start of the activationperiod could be determined from the temperature rise itself, but in thatcase it may be more difficult to determine if the system had failed.

FIG. 4 shows a chart 400 of the data collection process against atimeline, illustrating the creation of a record relating to theoperational period of an HVAC component. The sensor(s) measureenvironmental data values periodically (e.g. every 1 minute, 2 minutes,every 5 minutes etc.) and these values are held in a log, with eachvalue stored against the time at which it was measured. The log ofvalues is maintained for a predetermined preceding time period, so thatthe log provides a rolling window of data. For example, the log may bestored in a circular buffer where, as each new value is recorded, theoldest value is overwritten. For example, the log may be a 30-minutewindow of data, with only the values measured from the last 30 minutesbeing held in the log at any one time.

Row 410 shows the data log of environmental characteristic values at07:30 am. At 07:30 am the data log holds environmental characteristicvalues measured by the sensors in the last 30 minutes (i.e. the timeperiod 07:00 to 07:30 am). Row 420 shows the data log of environmentalcharacteristic values at 08:00 am. At 08:00 am the data log holds valuesfrom the last 30 minutes (i.e. the time period 07:30 to 08:00 am),however the values previously held in the log (e.g. those held at 07:30am) have been deleted.

At 08:00 am a first trigger occurs indicating the start of an activationperiod; for example, a signal is sent to the HVAC component to switch iton. Therefore at 08:00 am a data record relating to the operationalperiod of the HVAC component is created. The data record at 08:00 am isshown in row 430. At 08:00 am the record contains the values held in thedata log (i.e. environmental characteristic data values collected from07:30 to 08:00 am).

The sensors continue to measure environmental characteristic valuesperiodically (in this case every 2 minutes). As these values aremeasured they are added to the data record for this operational period.Row 440 shows the data values held in the record at 08:30 am, which arethe values measured between 07:30 am (30 minutes before the trigger) and08:30 am (the current time).

At 09:00 am a second trigger occurs, indicating the end of theactivation period; for example, a signal is sent to the HVAC componentto switch it off. This means that this operational period of the HVACdevice has come to an end. As can be seen from row 450, the data recordat 09:00 am contains values measured between 07:30 am and 09:00 am.

The environmental characteristic values continue to be measured afterthe off trigger. The first 30 minutes' worth of data values (i.e. thosebetween 09:00 and 09:30 am) are added to the data record relating to theoperational period of the HVAC component. Row 460 shows the data held inthe record at 09:30 am, i.e. all values recorded between 07:30 am (30minutes before the on trigger) and 09:30 am (30 minutes after the offtrigger). The record relating to the operational period of the HVACdevice between 08:00 and 09:00 am is now complete and can be analysed.

Following the completion of the record relating to the operationalperiod of the HVAC device the system reverts to logging the sensor datafor a rolling 30-minute window, until the start of the next activationperiod.

The log and record described in relation to FIG. 4 may be stored in theHVAC monitoring device 110, in the remote datacentre 180, or in both. Insome embodiments it may be advantageous to hold the data log in the HVACmonitoring device 110 only, and then transmit values to the remotedatacentre 180 only once an on trigger has been received. In such anembodiment, the data record relating to the operational period of theHVAC component may then be created and stored at the remote datacentre180 only, while the HVAC monitoring device 110 continues to store onlythe log of most recently collected environmental data values.

FIG. 5 shows a method 500 for monitoring “normal” behaviour of an HVACcomponent or device. Method 500 may be performed at step 204 of method200 (FIG. 2).

At step 510 a record relating to an operational period of an HVACcomponent is received. As described above in relation to FIGS. 3 and 4,this record will normally include data relating to an environmentalcharacteristic (e.g. temperature, humidity) measured while the HVACcomponent or device is in operation. The measurements of theenvironmental characteristic made in a period before and after the HVACdevice is operating may also be included in the record. The HVAC devicecould be e.g. a boiler, or an air conditioning unit.

At step 520 the record is analysed to compute a set of parametersrelating to the HVAC device (e.g. relating to its operation and/orperformance) and/or relating to the premises which the HVAC devicecontrols (e.g. relating to the environmental response of the monitoredspace), for that operational period. These parameters could for exampleinclude one or more of:

-   -   Change in value of measured environmental characteristic over        length of time for which the HVAC component is on (for example,        rate of change of room temperature or other characteristic over        activation period, such as rate at which the premises heats up        when the boiler is on (e.g. measured in degrees change per        hour));    -   Amount of energy required to maintain the environmental        characteristic at its target value, such as the heating required        to maintain a given target temperature at the premises (e.g. the        minutes per hour for which the boiler must be on);    -   Maximum/minimum achievable internal characteristic (e.g. the        maximum temperature is indicative of the steady state reached        when boiler is fully on);    -   Runtime characteristics of the specific system (e.g. periodic        oscillations in the environmental characteristic, which        correspond to the length of time an HVAC component (e.g. a        boiler) will run continuously before shutting itself off for a        period of time);    -   Typical time an environmental characteristic will take to begin        to change (e.g. temperature start increasing) after the start of        an activation period;    -   Length of time for which the HVAC component is switched on (or        is operating);    -   Rate of change of an environmental characteristic (e.g. room        temperature) at or near the beginning of an operational period;    -   Rate of change of an environmental characteristic (e.g. room        temperature) at or near the end of an operational period;    -   Summation of the rate of change over the whole set of        characteristic (e.g. temperature) measurements, (e.g. a positive        sum indicates warming);    -   Integral of difference between measured characteristic (e.g.        room temperature) and target setpoint (e.g. target temperature        set according to heating schedule);    -   Integral of difference between measured characteristic and        averaged rate of change of characteristic;    -   Time (as a proportion of the whole activation period) at which        the minimum (or maximum) characteristic value (e.g. temperature)        is measured;    -   Standard deviation (or other variability measure) of the        characteristic readings indicating the variability of the        characteristic over the activation period; and    -   Measures of the quality of the data being received, such as gaps        in data or periods in which no change in the measured        characteristic is detected.

Although the term “temperature” has been used in the examples above, theparameters could relate to other environmental characteristics that aremeasured, such as humidity.

Another example parameter that may be calculated is the Demand DegreeDay (DDD), which is the number of degree days taken between the targettemperature and the room temperature, i.e. the integral of thedifference between the target temperature (T_(target)) and the measuredroom temperature (T_(measured)) over time (t). Time (t) may be the wholeactivation period, or a sub-sample (e.g. 5 minutes), to show the changeover the activation period.

DDD=∫|(T _(target) −T _(measured))|dt

The trend of the DDD value shows whether a system is performingcorrectly to reach or not. It also helps indicate the user's preference,i.e. if they change the target target setpoint mid operation. The higherthe DDD the more the schedule is unfulfilled, indicating anunderperforming system. Similarly, the rate of change of the DDD over anactivation period will show, in the case of normal heating operation, areducing value as target temperature is reached. However, if the DDDrate increases then this is indicative of a failing system (see e.g.FIG. 8 below).

In some embodiments the computed parameter(s) are context-dependent andare mapped to one or more secondary characteristics, such as externaltemperature. For example, for any of the above parameters, a differentinstance of the parameter may be calculated from the operational periodsfor which the secondary characteristic has particular values or lieswithin particular ranges. As an example, one instance of the parametermay be calculated for operational periods when the external temperatureis 10-15° C., another parameter instance may be calculated when theexternal temperature is 15-20° C. and yet another for periods when theexternal temperature is 20-25° C. Alternatively, the secondarycharacteristic could be the time of year (e.g. due to winter beingindicative of colder weather than summer).

In some embodiments, the identification of the parameters can beperformed continuously as new data arrives, i.e. before the end of anactivation period and before the record relating to theoperational/activation period is complete. This means that it may bepossible to detect a failure before the end of an activation period.

At step 530 the identified parameters are analysed to decide whether therecord is indicative of an “expected” or normal behaviour of the HVACdevice. The identified parameters may be compared to trends expectedfrom the operation of that type of HVAC component in general.

Large divergence from an expected trend or inherent inconsistencies inthe data may indicate the behaviour is not “expected” or “normal”. Forexample, if the device is a boiler which has been switched on in orderto increase the room temperature, the measured room temperature would beexpected to increase over the time of the record (or at least while theboiler is on; the room temperature may decrease after the boiler isswitched off). If the measured room temperature decreases during theheating period, even some time after the boiler has been switched on,the behaviour is unexpected and further investigation may be required.As another example, heating periods in which the recorded roomtemperatures are similar at the start and end of the heating period areindicative of a “steady state” mode. This means either (1) heating hasreached the target temperature or (2) the house/premises has reachedsaturation. Scenario (1) is correct operation and “expected” behaviour.Scenario (2) indicates, if the recorded temperature is below the targettemperature, that the system may be underperforming; this is not“expected” behaviour. Saturation temperature can be affected by externaltemperature. For example, in some houses it might be possible to achievea temperature of 22 degrees Celsius when it is 14 degrees Celsiusoutside, but only 20 degrees Celsius when it is freezing outside. Thusknowledge of house performance can be useful to help determine whether afailure has occurred.

A variety of analytical techniques may be employed to determine whetherthe calculated parameters conform to “expected” behaviour or areindicative of potential faults or underperformance. Preferredembodiments employ machine learning techniques to derive aclassification model for classifying the system behaviour, as specifiedby the calculated parameter set. The classification model may be abinary model allowing classification into “expected” and “abnormal”classifications, with further analysis performed on activation periodsclassified as “abnormal” to determine the probable nature of the faultor other underperformance condition, as discussed further below.Alternatively the classification model could provide more than twoclassifications (e.g. including multiple broad failure classificationsin addition to an “expected” classification). Broadly speaking, such amachine learning approach may use parameter sets calculated for pastactivation periods (from the specific property under consideration orfrom multiple properties) and for which the relevant classification isknown (either through automated analysis or labelling by an operator) astraining samples to train the classification model.

In a preferred embodiment, a regression technique such as logisticregression may be used to combine two or more of the parametersdetermined at step 520 to better classify system behaviours and identifyfaulty behaviour. In an example of such an approach, the set ofparameters used defines a multidimensional feature space, and theregression algorithm computes a decision surface separating labelledtraining samples into the “expected” and “abnormal” classifications.Future samples are then classified based on the learnt decision surface.

Other information such as weather information (e.g. an outsidetemperature measurement and/or predicted weather forecast data from anexternal data source) may be used as an additional input, allowing aseasonal model to be applied—e.g. in colder months a house may beexpected to cool more quickly at the start of an activation period,before heat transfer from the heating system is fully functional.Seasonal knowledge can allow such a drop to not be confused as afailure. However, if there is a boiler failure, then even quickercooling than usual for the season may be expected.

In order to determine whether the record shows an “expected” behaviourit may be necessary to provide additional data, for example, the controlcommand given to the HVAC device and the reason for the control command(e.g. turn boiler on because the room temperature is below target). Inorder to make this determination the HVAC monitoring device 110 and/orthe remote datacentre 180 preferably receives the control schedule thathas been set for the HVAC system.

Where the parameters are calculated before the end of anactivation/operational period and before the record relating to theoperational/activation period is complete (e.g. continuously as new dataarrives), this analysis may also be performed before the end of theoperational period. This means that it may be possible to detect afailure before the end of an activation period.

If it is decided at step 530 (e.g. based on applying the classificationmodel to the computed parameter set) that the record shows an “expected”behaviour, the method proceeds to step 540. If it is decided the recorddoes not show expected behaviour a different process is followed(beginning at step 640 of FIG. 6).

At step 540 a standardised model of the behaviour of the HVAC componentand/or premises is adjusted or modified. For example, this may involveadjusting the learnt classifier based on the parameter set calculatedfor the currently analysed activation period, e.g. by adding thecalculated parameter set as a further labelled sample of expectedbehaviour to the set of training samples and retraining theclassification model (review and confirmation by a human operator may berequired before updating the model).

When a system is first installed, a “global model” of normal operationalperiods may be used initially. This may be in the form of a defaultclassifier based on a set of training samples for other HVACinstallations/properties. Subsequently the classification model is thenrefined based on the parameter data collected for the new system. Overtime, the model is therefore adapted to fit the particular premises andHVAC installation more accurately.

The data from these normal operation periods can be sampled foraccuracy. The normal operation periods can then be used in otheranalysis to monitor whether the system is operating correctly, asdescribed in more detail below.

It is possible to use the normal heating periods to check the expectedthermal characteristics of the environment. For example, the boiler runtime can be predicted based on outside/inside temperatures and a thermalmodel. This prediction can then be compared to the actual measured runtime to see if the system performs as expected or takes longer. If theHVAC system is coming on at unexpected times this can also be seen.

FIG. 6 shows a method 600 for identifying a fault or failure in an HVACcomponent. Method 600 may be performed at step 208 of method 200 (FIG.2) to analyse data relevant to an operational period of an HVACcomponent to identify a suspected fault. The first three steps 510, 520,530 of method 600 are the same as in the method 500 of FIG. 5; a recordrelating to an operational period of an HVAC component is received, oneor more parameters are determined from the record and then the one ormore parameters are analysed to decide whether it is indicative of an“expected” response of the monitored environmental characteristic thatwould be seen with normal, non-faulty operation of the HVAC device(thus, the calculated parameters are preferably the same set asdetermined in step 520 of FIG. 5). Examples of records identified asshowing unexpected behaviour include, for example, situations wherethere is a drop in room temperature over a heating period (e.g. a periodduring which the boiler has been instructed to provide hot water for theheating system), a rise in room temperature over a cooling period (e.g.while an air conditioning unit is switched on), and a rise in roomtemperature during a hot water heating period (but whilst the centralheating is switched off).

The determination that the record does not conform to “expected”behaviour may be made based on the same classification model asdiscussed above. Thus, classification is performed as discussed above(by applying a learnt classification model, e.g. by comparing theparameter set for the current activation period to a decision surface inan n-dimensional decision space), but in this case yields an “abnormalbehaviour” classification.

If the record does not indicate “expected” behaviour then the heatingperiod is identified as a potential failure of the HVAC system forfurther investigation. Therefore the method progresses to step 640 inwhich the one or more parameters relating to the activation period ofthe HVAC component are analysed further to identify what the suspectedfault may be.

The one or more parameters can include, for example, one or more ofthose mentioned at step 530 above.

At step 640 the existence of a suspected fault in the HVAC system isidentified. This can include identifying the type of fault (i.e.diagnosis of the specific issue with the HVAC component). In some casesit may not be identifiable from the data, so there may be an“unidentified” fault type diagnosed.

At step 650 the parameters identified at step 530 and any identificationof the fault made at step 640 are used to assign the behaviour of theoperational period a failure classification. For example, theclassifications may be “critical” and “non-critical” failures. Therecould (also) be a category for unconfirmed failures which requirefurther investigation or testing in order to identify the specificfailure. Classified failures can then be dealt with in different waysdepending on the failure classification assigned.

As in the FIG. 5 case where the activation period is classified asconforming to “expected” behaviour, in the FIG. 6 case where abnormalbehaviour is identified, the set of parameters may be fed back as atraining sample to allow the classification model to be refined. Thismay be done automatically, or after confirmation by a human operator(which may serve to prevent propagation of classification errors).

As mentioned in relation to the methods 200, 300 of FIGS. 2 and 3, theprocesses 500, 600 of FIGS. 5 and 6 may be conducted at the HVACmonitoring device 110 or at the remote datacentre 180. For example, theremote datacentre 180 may include an analysis module at which methods500, 600 are performed. In some embodiments the methods 500, 600 may beperformed at both the HVAC monitoring device 110 and at the remotedatacentre 180, or some steps may be performed at one whilst other stepsare performed at the other. In a preferred embodiment the methods 500,600 for analysing normal and faulty behaviour of an HVAC component areperformed at the remote analysis server 180.

If the analysis at steps 520 and/or 530 is performed at the remotedatacentre 180, information and records from other HVAC components andother premises may be used in order to determine whether the behaviouris as expected.

Specific fault types that can be identified at step 640 may include, forexample: incorrect wiring, valve leakage and heat leaking from hot watersystem to space heating system. FIG. 7 shows an example of possiblefailure classifications that may be made at step 650 once a specificfailure type has been identified. The classifications include criticalfailures 710, non-critical failures 720 and failures which areunidentified or require further investigation 730. In this case thenon-critical failures category 720 includes the unidentified faults 730(i.e. classification 730 is a subset of classification 720). However insome embodiments the unidentified failure classification 730 may be aseparate classification.

Critical failures 710 may include: complete failure of a component;incorrect wiring (inverse/swapped control); or extensive valve leakage.These may cause damage to the premises, or result in a system which doesnot function at all.

Non-critical problems 720 which can be identified by the HVAC monitoringsystem include: air accumulating in radiators; valve degradation;boiler/HVAC component switched off and water flowing from Hot Water (HW)system to Space heating (SH) system. These problems with an HVAC systemwould not cause an instant “failure”, however they may cause degradationor under performance over time, which would show up as gradual changesin the way the thermal environment behaves.

Unidentified faults 730 may, for example, relate to operational periodsof the HVAC component in which the parameters diverge from thestandardised normal parameters for the HVAC component and/or premises,but which do not seem to have the characteristics of any specific knownfault. Running a test cycle may give further details of the failurecondition.

Specific examples relating to the identification of HVAC faults aredescribed in detail below in relation to FIGS. 8 to 11.

FIG. 8 is a plot showing a temperature data set indicative of a typical“catastrophic”—i.e. complete—boiler failure. Line 810 shows the targetroom temperature setpoint; line 820 shows the boiler call for spaceheating (this is binary 1/0, i.e. on or off); line 840 shows theinternal room temperature.

The target temperature 810 has been set to 19° C. from the start of thedata set (at 17:30) until 07:30 the next day. The measured roomtemperature 840 at 17:30 is between 19° C. and 20° C. (i.e. above thetarget temperature).

At around 18:30 the recorded room temperature 840 drops below 19° C.,which triggers a Boiler On command as space heating (SH) is requested bythe HVAC controller in order to maintain the target temperature 810(e.g. by placing a call for SH control signal 820 in an “on” state). Asis shown in FIG. 8, the logged thermal data from the preceding timewindow is stored in the data object for this new heating period and anynew temperature data points are appended to the data object in realtime. In this case 60 minutes' worth of data preceding the activationperiod is shown, beginning at around 17:30. However in some cases only30 minutes' worth of data preceding the activation period will actuallybe added to the data record. The thermal data can be updated in realtime (e.g. every 2 minutes, as the temperature sensor records thethermal data).

The boiler was commanded to provide SH, but the room temperature 840continues to fall to around 16° C. between 18:30 and 07:30 the nextmorning. This is because the boiler is no longer generating hot water.An alert would be sent to the user indicating this and asking if theyhad manually turned off their boiler.

At 07:30 the pre-programmed target temperature 810 changes from 19° C.to only 5° C. (this may be because the user does not require heating tobe on during the day). This triggers a “Boiler Off” command (e.g. byplacing the call for SH control signal 820 in an “off” state) and, thefollowing 30 minutes of temperature (or thermal) data is logged andappended to the data object or record relating to the operational periodof the boiler.

FIG. 9 shows the case where the boiler wiring has been inverted atinstallation. Line 910 shows the target room temperature setpoint; line920 shows the boiler call for space heating (this is binary, i.e. on oroff); line 940 shows the internal room temperature; and line 950 showsthe boiler command for DHW did not occur (zero throughout).

The target temperature 910 at the beginning of the data object (13:00)is 22° C. and the recorded temperature is just below this so the boilercall for space heating (SH) 920 is on, but the measured room temperature910 is decreasing.

Just before 14:00 the target temperature 910 is increased to 23.5° C.and the boiler call for SH 920 remains on. The recorded room temperature940 continues to reduce to around 21° C., where it levels out for around2 hours, and then gradually decreases again due to the cooling externaltemperatures in the evening. The temperature 940 continues to decreaseto a low of 16° C. at around 23:00, and then gradually begins toincrease again to around 17° C. at midnight.

Just after midnight the target temperature 910 is reduced to 16° C. Asthe measured room temperature 940 exceeds the target temperature thistriggers deactivation of the call for SH signal 920 to the boiler. Themeasured room temperature 940 suddenly rapidly rises from 17° C. toaround 22.5° C. between 00:00 and 00:30. After around 00:30 the measuredroom temperature begins to fall again.

In this example, a temperature decrease is thus observed during a callfor heat and a temperature increase after at the end of the heatingperiod. As the boiler command seems to be inverse to the temperaturegradient in the house this indicates that the boiler wiring seems to beinverted, i.e. an installation error.

FIG. 10 is a graph showing temperature for an underpowered orincorrectly balanced system. Line 1010 shows the target room temperaturesetpoint; line 1020 shows the boiler call for space heating (this isbinary, i.e. on or off); line 1040 shows the internal room temperature;and line 1050 shows the boiler call for Domestic Hot Water (which isoff, zero, throughout).

The room temperature 1040 at the beginning of the dataset (18:00) isaround 19° C. and the target temperature 1010 is 17.5° C., so the boilerSH is switched off (line 1050 is at zero). At 18:45 the target roomtemperature setpoint 1010 increased to 20° C., which triggers the boilerSH on signal 1020. The measured room temperature 1040 graduallyincreases and reaches 20° C. at 20:30, so the boiler is switched off.

The measured room temperature 1040 just after 21:00 is slightly abovethe target temperature 1010 of 20° C. so the boiler is off and SH is notbeing called. The measured temperature 1040 then drops slightly below20° C., which activates the call for SH signal 1020 and the measuredtemperature 1040 rises to above 20° C. at around 21:30. The call for SHsignal 1020 is then deactivated.

The measured room temperature 1040 then gradually begins to fall tobelow 20° C. just after 22:00, which turns the call for SH 1020 on. Themeasured room temperature 1040 continues generally to drop over the next8 or so hours and does not reach the target temperature 1010 of 20° C.There are slight oscillations in the measured room temperature 1040during this time of around 0.5° C. with a period of about 1 hour. Thisis because over night the external temperature increases the coolingrate of the property above the rate at which the boiler can produceheat, causing the room temperature 1040 to lower gradually with anoscillation period related to the boiler firing maximum runtime (in thiscase ˜30 minutes). This shows that the system is underpowered orincorrectly balanced.

At around 05:30 the target temperature is reduced to 18° C. Since themeasured room temperature 1040 is above 18° C., the call for SH 1020 isswitched off and the following 60 minutes of temperature (or thermal)data is logged and appended to the data record for the activationperiod.

FIG. 11 shows temperature data for a system in which the roomtemperature is affected by calls for Domestic Hot Water (DHW). Line 1110shows the target room temperature setpoint; line 1120 shows the boilercall for space heating (this is binary, i.e. on or off); line 1130 showsthe call for DHW (also binary encoded); line 1140 shows the internalroom temperature.

The target room temperature 1110 rises from 5° C. to 20° C. at 01:30,above the measured room temperature 1140 of ˜15° C., which continues todrop. This triggers the boiler call for SH 1120. The following eveningthe target setpoint schedule drops to 5° C. between 23:00 and 00:30,temporarily stopping the call for SH, but no effect is seen on the roomtemperature data 1140. In spite of the fact that the call for SH is onalmost continuously, the measured room temperature 1140 stays betweenabout 13° C. and 16° C. and does not get anywhere near the targetsetpoint of 20° C. This shows that there may be a boiler fault, or theSH capacity of the boiler may have been manually switched off. It isnoted that in such cases it may not be possible for the system todistinguish between a boiler that has been manually switched off and aboiler that has completely failed.

At around 06:30 the call for DHW 1130 signal is activated for 1.5 hours.In this case faulty valves in the water and heating system may havecaused hot water from the domestic hot water supply to leak into thespace heating system for the radiators. Therefore shortly after the DHWcall 1130, the measured room temperature 1140 rises rapidly from 14° C.to ˜16.5° C. as the temperature of the water in the radiators hasincreased. When the DHW call 1130 ends at around 08:00 the recorded roomtemperature 1140 begins to drop again to below 15° C.

The call for DHW signal 1130 is also activated between 17:00 and 19:30,again causing a sharp rise in the measured room temperature 1140 duringthose hours, followed by a subsequent fall.

This pattern of temperature rises during DHW call is also shown to berepeated the following day with a steady gradual descent in temperature.

This shows the room temperature is very low and is correlated with (andhence probably affected by) the calls for DHW, rather than by the SHcommand (which is mostly on, apart from when the target room temperatureis at 5° C.). This indicates a system with leaks between the DHW systemand the SH system, so that room temperature rises come from the domestichot water signal causing the water in the radiators to heat up and henceheat the room.

In an alternative situation, if it is observed that the room temperatureis affected by calls for hot water, this may be due to faulty wiring.For example, it may be the case that the call for DHW signal is wired tothe SH inputs, so the thermostat may send a signal to activate waterheating but instead the space heating will be activated. In thissituation there would likely be a significant increase in roomtemperature when the DHW is called.

Another scenario that could be detected would be the call for domestichot water affecting the room temperature because heat from the hot watertank and/or pipes leaks into the room. Operating the boiler to heatwater would result in a small amount of heat leaking into the room, fromthe boiler/pipes/or the tank itself, thus the room temperature wouldincrease slightly. This could occur during normal (correct) hot wateroperation (possibly indicating inadequate insulation).

The system shown in FIG. 11 has a greater DDD than that in FIG. 10. Thisindicates that the system of FIG. 11 is underperforming more badly thanthe system of FIG. 10, which is almost at the target setpoint.

Whilst FIGS. 8-11 illustrate some examples of failures that may bedetected and classified by analysis of temperature data sets inaccordance with the described techniques, these examples are notexhaustive.

FIG. 11B shows an example of temperature data for a heating system thatis operating normally. Line 1110′ shows the target room temperaturesetpoint; line 1120′ shows the boiler call for space heating (this isbinary, i.e. on or off); line 1140′ shows the internal room temperature.

Initially the room temperature 1140′ is around 18° C. and the targetsetpoint 1110′ is 16° C., so the boiler call for space heating isswitched off. At 21:00 the target setpoint 1110′ increases to 20.5° C.This causes the boiler call for space heating 1120′ to switch on. Themeasured room temperature 1140′ steadily rises between 21:00 and 03:30,at which point it reaches the target temperature of 20.5° C. This causesthe boiler call for space heating 1120′ to switch off. This shows a risein room temperature of around 2.5° C. in around 6.5 hours (i.e. a rateof 0.4° C. per hour). This may be used to build up a thermal model ofthe premises and/or modify a standard global model, which can be used infuture determinations of faults.

Once detected and classified, classified failures can be labelled andplaced on failure-specific message queues at the datacentre.

Failures, once suspected or identified, can be dealt with appropriately.For example:

-   -   Catastrophic failures trigger alerts to the user quickly. These        may be messages sent directly to the user's mobile device, email        address etc. If the user is also signed up to a repair service,        the service engineers can be alerted at the request (or        pre-request) of the home owner.    -   Houses with a heating system that is unable to maintain an        adequate target temperature can be monitored for continued        failure (e.g. to rule out manual ventilation etc.)    -   A user can be messaged when certain criteria are surpassed (e.g.        the notification criteria may indicate that a failure must be        sustained for some minimum time duration and/or a certain number        of failures must be recorded, e.g. the failure must reoccur over        a given number of days).

FIG. 12 shows a flow chart 1200 of a process for informing the user of afailure or fault in the HVAC system once it has been identified. Process1200 starts at step 1210 which continues on from the end of FIG. 6 afterthe behaviour of the HVAC component has been classified in step 650. At1220 a determination is made as to whether the identified failure hasbeen classified as critical. If the failure is classified as criticalthe process continues to 1225.

At 1225 a determination is made as to whether the user is subscribed toa repair service. If the user is subscribed to a repair service theprocess continues to step 1230.

At step 1230 the system informs the user of the critical failure andrequests permission to request an engineer. This may be performed bysending a message to the user's phone, tablet or other electronic devicesuch as user device 190 (see FIG. 1). Alternatively, the message may bedisplayed on a user interface within the home, such as user device 192(see FIG. 1). The message may also ask the user if they have e.g.switched the HVAC component off manually, which could result in a datarecord that looks like a complete failure.

At 1235 a determination is made as to whether the user has givenpermission to request an engineer. If permission has been given, anengineer will be requested at step 1240. Details of the failure may alsobe sent to the engineer. For example data from the record relating tothe operational period of the HVAC component may be sent to theengineer. In addition, standardised normal parameters of the HVACcomponent and/or records showing expected behaviour may also be sent tothe engineer. This may allow the engineer to have prior knowledge of thesystem's mode of failure and the engineer may be able to fix thecomponent more efficiently.

If the user did not give permission for the system to request anengineer at 1235 then details of the failure are recorded at step 1255and the system continues to monitor the HVAC component. If the criticalfailure that has been identified as dangerous or likely to cause damageto a premises, an instruction may also be sent to switch the HVACcomponent off.

If at step 1225 it was determined that the user is not subscribed to arepair service, the user is simply informed of the critical failure ofthe HVAC component at step 1250. As in step 1230, the user may beinformed of the failure via a message to their smart device, such as amobile phone, and/or by a message displayed on a user interface at thepremises.

Once the user has been informed of a failure of the HVAC component atstep 1250, the process continues to step 1255 where details of thefailure are logged and monitoring of the HVAC component continues.However, once again if the failure is determined as dangerous or likelyto cause damage the HVAC component may be disabled.

If it is determined at step 1220 that the failure is not classified ascritical the method continues to step 1260. This means the fault will bea non-critical fault and that it is not confirmed that the failure typewill cause an instant, complete failure of the system or HVAC component.Non-critical faults may cause degradation or underperformance over time.Examples of non-critical failures include air accumulating in radiatorsand valve degradation. At 1260 it is determined whether the failure isclassified as “unidentified”. This would mean that the specific faulttype of the HVAC component cannot be identified or confirmed based onthe record relating to the operational period of the HVAC component.

If the failure is determined not to have been unidentified at step 1260,the process continues to step 1265, where a determination is made as towhether the non-critical but identified fault has occurred with apredetermined frequency, more than a predetermined number of times orfor more than a predetermined length of time continuously. Thepredetermined level for the frequency of failures recorded, number offailures recorded or duration of the failure may be fixed or userconfigurable. If this predetermined level has been reached the methodcontinues to step 1225 where it is determined whether the user issubscribed to a repair service. The process then continues as describedabove. If the failure has not reached the predetermined level details ofthe failure are recorded and monitoring of the HVAC component continuesat step 1255, also as described above.

On initial installation, the monitoring system has no prior knowledge ofthe HVAC system installed, or of the premises. In one embodiment thesystem can learn about “good” operating conditions based on a number ofsuccessful activation periods. Metrics can be built on this monitoringto better refine the parameters by which future activation periods aredeemed success or failure. For example some houses take 4+ hours tostart warming up after the boiler is switched on. This might look like afailure for 4 hours, but if this system is known to be very slow thenthe monitoring can learn to expect that. Feedback from a user/operatorcan also be used to inform the monitoring system that what might looklike a failure is not a failure.

Step 1255 may, for example, comprise adding the Demand Degree Day, DDD,(see above for explanation) recorded for the operational period to thetotal DDD value already held in the system for that HVAC component. Thehigher the DDD the more the schedule is unfulfilled, indicating anunderperforming system. The continued monitoring of the HVAC componentmay include analysing the DDD over time to determine whether it isincreasing (which would indicate the HVAC component is degrading).

Alternatively, step 1265 could include adding the Demand Degree Day,DDD, (the number of degree days taken between the target temperature andthe room temperature) recorded for the operational period to the totalDDD already held in the system for that HVAC component and determiningwhether the total DDD is above a certain threshold.

If the failure was classified as unidentified at step 1260, it meansthat further analysis is required to identify what the fault with theHVAC component might be. Therefore the process continues to step 1270where it is determined whether there is a test that can be performed toidentify the failure. In some cases, the HVAC monitoring system may haveidentified a possible failure type but there may not yet be enough datato confirm it so the test may comprise gathering more data. If there isa test that can be performed to identify the failure the processcontinues to step 1275. At step 1275 the user is informed that anunidentified or unconfirmed failure has occurred and they are asked forpermission to perform a test of the HVAC system. The user may beinformed of the specific test that is proposed. As before the user maybe informed by a message to their smart device or on an in-home display.The method then continues to 1280 where it is determined whether theuser has given permission to perform the test.

If the user has given permission for the test to be performed, themethod proceeds to step 1290 and the test procedure is begun. Moreinformation about test procedures is set out below.

If at 1280 it is determined that the user has not given permission toperform a test the method continues to step 1255 where details of thefailure are recorded and the HVAC component continues to be monitored.

Some failure modes might require a test procedure to confirm the failureor fault has been identified correctly. The user may be messaged with asuggestion that the system performs such a test, as described inrelation to steps 1270 and 1275 of FIG. 12 above. In other circumstancesa test procedure may be initiated by an engineer upon installing orrepairing the HVAC component in order to ensure the HVAC component hasbeen correctly installed or successfully repaired.

In another embodiment, given a pre-described knowledge of the house, abuilder or engineer could install the HVAC device or system and then runone or more defined tests to check the operation of the HVAC system.This could confirm that the thermal characteristics of a(new/refurbished) house are as expected. Alternatively, the test couldconfirm that the HVAC component is installed correctly. In the lattercase, the test procedure may take into account standardised parametersof the premises which have been obtained from records relating toprevious operational periods of other HVAC devices at the same premises(e.g. a previously installed HVAC device which is now being replaced).

An example of a test procedure 1300 will now be described in relation toFIG. 13. If a user accepts or requests a test procedure, the testprocedure will commence at step 1290 (see also FIG. 12).

At step 1310 an instruction is sent to the HVAC component to overridethe user's pre-programmed environmental control schedule. The test willlast for a certain test period, which may be predetermined, or it maydepend on the results of the test. The instruction may be sent as amessage to the HVAC controller 120, or it may be sent directly to theHVAC component in question. For example, a message can be sent to aboiler controller (e.g. a smart thermostat) to override the user'sschedule temporarily and run the test procedure by switching spaceheating on for 1 hour (the “test period”). Space heating for 1 hourwould be expected to generate a specific change in room temperature(which may be calculated based on the standardised “normal” parametersof the HVAC component obtained in step 540 of method 500, see above).

At step 1320 the HVAC component is monitored by collecting data relevantto the test period. Normally this monitoring process would be conductedin the same manner as when a record of an operational period of the HVACcomponent is created, for example as described in relation to FIGS. 3and 4. This record relating to the test period may, for example, includedata collected during a pre-set period preceding the test period, aswell as during a pre-set period subsequent to the test period.

At step 1330 the record relating to the test period of the HVACcomponent is analysed to identify parameters of the HVAC componentand/or the premises. As described above in relation to step 520, theseparameters may for example include the rate at which the premises heatsup when the boiler is on (i.e. degrees change per hour).

At step 1340 the identified test period parameters may be compared withstandardised “normal” parameters, obtained in step 540, in order todetermine how much the test behaviour of the HVAC component divergesfrom normal behaviour. However this step may be omitted (particularly ifno “normal” standardised parameters are available).

At step 1350 a specific failure mode of the HVAC component is confirmedor rejected. If the system had previously identified what the failurecould potentially be (i.e. the operation period record showed some butnot all the characteristics of a specific failure mode), the analysis ofthe test may be positive and it is possible to confirm that the HVACdevice has failed in the suspected way. Alternatively, the test may showa negative result, which would indicate that the HVAC device is notexperiencing the suspected fault/failure. If the failure had been in theunidentified category previously, the test results may allow the faulttype to be identified and/or confirmed.

The confirmation or rejection of a failure type may be based on theresults of the test period, as well as results of the operational periodwhich triggered the test cycle and/or data from previous operationalperiods. It may also be based on identifying known trends found in thedata of the record relating to the test period, for examplepre-programmed fixed trends which are generic to all HVAC components(rather than to the specific monitored component and premises).

The user would then be messaged with the test result, for example by amessage to their email address, to their personal device 190 (e.g.smartphone or tablet) or to a user interface within the premises 192. Ifthe test cycle 1300 resulted in the confirmation of a failure mode, themethod may proceed to step 1225 of FIG. 12, so that a message about afailed test can be sent to the user which incorporates a responsesection for authorising a request for an engineer to visit.

FIG. 14 illustrates a hardware architecture of the HVAC monitoringdevice 110 that may be provided for monitoring an environmental controlsystem, in conjunction with an HVAC controller (e.g. thermostat). TheHVAC monitoring device 110 includes a processor 1400 together withvolatile/random access memory 1402 for storing temporary data andsoftware code being executed. Random access memory 1402 may be used tostore continuously the rolling log of data from environmental sensors(e.g. temperature data). Persistent storage 1404 may store controlinformation 1408, including the control schedule(s) programmed by theuser into the HVAC controller 120 (see FIG. 1). Persistent storage 1404may include other software and data, such as an operating system, devicedrivers, software configuration data, historical temperature measurementdata, and the like.

As mentioned above in relation to FIG. 1, the control schedules may bereceived from the HVAC controller 120 or from the wireless receivers130, 132, 134 (FIG. 1). In this case (the control schedules not beingstored in the HVAC monitoring device 110), the HVAC monitoring device110 may receive a message from one of the receivers 130, 132, 134 orfrom the HVAC controller 120 when the HVAC components are switched on oroff. This message may also include some details of the environmentalcontrol schedule (e.g. what the target temperature or humidity is) sothat only temporary copies of the information are stored at thethermostat (e.g. in memory 1402).

Communication with the wireless receivers 130, 132, 134, the HVACcontroller 120 and the sensors 112, 114 (FIG. 1) occurs via a wirelessnetwork interface 1410 and wireless transceiver 1412.

Environmental sensors 112, 114 (FIG. 1) measure the ambient temperatureand humidity and provide the environmental characteristic information toHVAC monitoring device 110 via the wireless transceiver 1412 and thewireless interface 1410. This information is passed to the processor1400, which stores the information in memory 1402 and/or persistentstorage 1404 for use in controlling the heating system.

As explained above, in some embodiments the sensors may be incorporatedinto the HVAC monitoring device.

The device components are interconnected by a data bus (this may inpractice consist of several distinct buses such as a memory bus and I/Obus).

While a specific architecture is shown, any appropriatehardware/software architecture may be employed. For example, externalcommunication may be via a wired network connection.

As mentioned above, instead of being provided separately as anadditional “Internet of Things” component and linked into the smartthermostat ecosystem via the wireless local area network (WLAN) at thepremises the HVAC monitoring device 110 could be embedded within a smartthermostat (HVAC controller 120).

FIG. 15A illustrates a hardware architecture of the remote datacentre(analysis server 180) shown in FIG. 1. The analysis server 180 comprisesat least one communication interface 1512 for connection with theInternet 170. Via the connection with the Internet 170, the remotedatacentre 180 can communicate with HVAC monitoring devices 110 (FIG. 1)in numerous different premises.

The analysis server 180 includes a processor 1500 together withvolatile/random access memory 1502 for storing temporary data andsoftware code being executed. Random access memory 1502 may be used tostore data temporarily (for example the rolling log of data fromenvironmental sensors in embodiments in which the sensor data for thelog is continuously sent to the analysis server 180 from the HVACmonitoring devices 110).

Persistent storage 1504 (e.g. in the form of disk storage or FLASHmemory) may persistently store control information, such as logic foranalysing environmental data.

FIG. 15B illustrates a software architecture of the analysis server 180shown in FIG. 1.

A data stream 1510 is sent from each house or property to the analysisserver 180. Each individual house is monitored by a different datacollection thread 514 at the analysis server 180. The analysis server180 may maintain a log of recorded environmental characteristic valuesand target characteristic values over a given time period. For example,the log may consist of room temperature readings for the preceding 30minute period. In other embodiments, the HVAC monitoring device may onlypass this data onto the remote datacentre 180 once the HVAC componenthas been activated and an activation period has begun.

An alert can be triggered by receipt of an activation (e.g. “Boiler On”)command, or characteristic diverging from the scheduled/requested target(e.g. room temperature falling below the target temperature). Onactivation of the activation trigger, the logged data from the preceding30 minute time window is stored as a “data object” 1516; any newtemperature data points are appended to the data object in real time.Another alert is triggered by a deactivation (e.g. “Boiler Off”)command, or the environmental characteristic reaching its target (e.g.room temperature rising above the target temperature).

Once a data object 1516 has been created for an operational period of anenvironmental control system the data object 1516 is sent to a messagequeue 1518 (which may be a real-time message queue), and subsequentlypassed to an analysis module 1520 within the analysis server 180 foranalysis. The analysis module 1520 analyses the monitored environmentalcharacteristic values (e.g. temperature values) recorded in the dataobject 1516 to identify and classify underperformance or failureconditions as previously described.

A small random sample of all classified heating periods may beanonymised and made visible to an operator of the analysis server 180for validation. Properties where a failure has been identified can beput on a watch list for more regular future random sampling by anoperator.

Whilst described mainly in the context of domestic HVAC systems, theinvention may also be used in office environments or anywhere withtemperatures or other environmental characteristics to be controlled.

The above embodiments and examples are to be understood as illustrativeexamples. Further embodiments, aspects or examples are envisaged. It isto be understood that any feature described in relation to any oneembodiment, aspect or example may be used alone, or in combination withother features described, and may also be used in combination with oneor more features of any other of the embodiments, aspects or examples,or any combination of any other of the embodiments, aspects or examples.Furthermore, equivalents and modifications not described above may alsobe employed without departing from the scope of the invention, which isdefined in the accompanying claims.

1. A method of monitoring the performance of an environmental controlsystem arranged to control at least one environmental characteristic inan environment, the method comprising: periodically recording sensordata relating to an environmental characteristic from at least oneenvironmental sensor in a sensor log; identifying an activation periodduring which an environmental control system is expected to be activatedto control the environmental characteristic; in response to identifyingthe activation period, generating a data set of sensor data measuredduring the activation period relating to the environmentalcharacteristic based on the sensor log and recording the data set ofsensor data; receiving control data indicating a target value configuredat the environmental control system for the environmentalcharacteristic; analysing the data set in dependence on the target valueto determine whether the sensor data within the data set is consistentwith an expected response of the environmental characteristic during theactivation period; and detecting an underperformance condition inresponse to determining that the sensor data within the data set is notconsistent with the expected response.
 2. A method according to claim 1,wherein identifying the activation period comprises detecting a startand/or an end of the activation period.
 3. A method according to claim2, wherein one or both of the start and the end of the activation periodare detected in dependence on a control signal used to control theenvironmental control system.
 4. (canceled)
 5. (canceled)
 6. A methodaccording to claim 1, wherein one or both of a start and an end of theactivation period are detected in dependence on a change in the targetvalue specified in the control data and/or a difference between thetarget value and a current value of the environmental characteristic. 7.A method according to claim 1, comprising one or both of: inferring astart of the activation period in response to detecting a currentmeasured value of the environmental characteristic not meeting thetarget value; inferring an end of the activation period in response todetecting a current measured value of the environmental characteristicmeeting the target value.
 8. A method according to claim 1, whereinreceiving control data comprises accessing a control schedule configuredat the environmental control system, the control schedule specifying oneor more control set points, each control set point specifying a targetvalue for the environmental characteristic applicable at a respectivetime.
 9. (canceled)
 10. A method according to claim 1, wherein theenvironmental characteristic is a temperature of the environment, andwherein a control set point or the target value specifies a targettemperature for the environment.
 11. A method according to claim 1,wherein the analysed data set comprises one or both of: sensor data fora period preceding a start of the activation period; sensor data for aperiod following an end of the activation period.
 12. (canceled)
 13. Amethod according to claim 1, comprising, in response to identifying astart of the activation period: adding previously recorded sensor datafor a predetermined duration prior to the start of the activation periodfrom the log to the data set for analysis; adding further sensor datareceived during the activation period to the data set; after detectionof an end of the activation period, continuing to store sensor datareceived from the environmental sensor to the data set; and terminatingrecording of sensor data to the data set a predetermined duration afterthe end of the activation period.
 14. A method according to claim 1,wherein the analysing step comprises determining whether the sensor datawithin the data set indicates that the target value is substantiallyattained and/or maintained during the activation period, and wherein thedetecting step comprises detecting an underperformance condition inresponse to the target value not being substantially attained and/ormaintained during the activation period.
 15. (canceled)
 16. A methodaccording to claim 1, wherein the analysis of the data set determinesunderperformance conditions based on one or more of: a duration of theactivation period; a change of the environmental characteristic over thecourse of the activation period; a rate of change of the environmentalcharacteristic during the activation period; a difference between one ormore measured values of the environmental characteristic during theactivation period and the target value, and/or an average or integral ofsaid difference over the activation period.
 17. A method according toclaim 1, wherein analysing the sensor data to determine whether thesensor data within the data set is consistent with an expected responseof the environmental characteristic during the period comprisesdetermining whether the sensor data within the data set meets at leastone of a set of one or more predetermined fault conditions.
 18. A methodaccording to claim 17, wherein the environmental characteristic istemperature, the predetermined fault conditions comprising one or moreof: detecting a lack of increase in temperature or a reduction intemperature during the activation period, the activation period intendedto increase the temperature; detecting a lack of reduction intemperature or an increase in temperature during the activation period,the activation period intended to reduce the temperature; detecting asteady state temperature achieved or maintained during the activationperiod which differs from a target value specified in a control scheduleby more than a threshold amount; detecting a temperature changeindicative of activation of the environmental control system in a periodimmediately preceding or following the activation period; detecting anirregular pattern of temperature variation during the activation period;detecting a correlation between environmental temperature variationsduring the activation period and the operation of, or a control signalintended for the operation of, a system other than an environmentaltemperature control component intended to regulate the environmentaltemperature.
 19. A method according to claim 1, comprising alerting auser associated with the environmental control system in response todetecting the underperformance condition, the alerting comprising one ormore of: displaying an alert on a display associated with theenvironmental control system; and transmitting an alert message to auser device associated with the user.
 20. (canceled)
 21. A methodaccording to claim 1, comprising, in response to detecting theunderperformance condition, initiating a test procedure for testing theenvironmental control system, wherein the test procedure comprises:activating the environmental control system; measuring changes in theenvironmental characteristic in response to activation of theenvironmental control system; and performing further analysis ofmeasured sensor data relating to the environmental characteristic toidentify, quantify and/or classify the underperformance condition. 22.(canceled)
 23. (canceled)
 24. A method according to claim 1, comprisingperforming the analysis by an analysis module asynchronously with thedata collection.
 25. A method according to claim 1, comprising, at adata collection module: detecting the activation period and storing thesensor data set relating to the activation period in a data object; andat an analysis module: receiving the data object and performing theanalysis of the sensor data.
 26. (canceled)
 27. (canceled) 28.(canceled)
 29. A method according to claim 1, comprising, in response todetermining that the data set is consistent with the expected response,analysing the data set to determine one or more thermal parameters ofthe environmental control system and/or the associated environment, andusing the one or more thermal parameters in the analysing step for asubsequent activation period.
 30. (canceled)
 31. A system for monitoringthe performance of an environmental control system arranged to controlat least one environmental characteristic in an environment, the systemcomprising: a monitoring device comprising: a processor for identifyingan activation period during which the environmental control system isexpected to be activated to control an environmental characteristic, andgenerating, in response to identifying the activation period, a data setof sensor data measured during the activation period relating to theenvironmental characteristic based on the sensor log; a memory forrecording the data set of sensor data measured during the activationperiod relating to the environmental characteristic; and an interfacefor transmitting the data set to an analysis server for analysis; andthe analysis server comprising: an interface for receiving from themonitoring device the data set of sensor data relating to theenvironmental characteristic measured during an activation period of theenvironmental control system; and a processor for analysing the data setin dependence on the target value to determine whether the sensor datawithin the data set is consistent with an expected response of theenvironmental characteristic during the activation period; and detectingan underperformance condition in response to determining that the sensordata within the data set is not consistent with the expected response.32. (canceled)
 33. (canceled)
 34. A computer-readable medium comprisingsoftware code adapted, when executed on a data processing apparatus, toperform the method of claim
 1. 35. (canceled)
 36. (canceled)